1export const supabaseVectorIntegrationSpec = defineIntegration({
2  meta: {
3    key: 'vectordb.supabase',
4    version: '1.0.0',
5    category: 'vector-db',
6    title: 'Supabase Vector Database (pgvector)',
7    description:
8      'Supabase integration for embedding storage and vector similarity search using pgvector.',
9    domain: 'ai',
10    owners: ['platform.ai'],
11    tags: ['vector-db', 'supabase', 'pgvector'],
12    stability: StabilityEnum.Beta,
13  },
14  supportedModes: ['managed', 'byok'],
15  capabilities: {
16    provides: [
17      { key: 'vector-db.search', version: '1.0.0' },
18      { key: 'vector-db.storage', version: '1.0.0' },
19    ],
20    requires: [
21      {
22        key: 'ai.embeddings',
23        optional: true,
24        reason:
25          'Required when vectors are generated by a hosted embedding provider.',
26      },
27    ],
28  },
29  configSchema: {
30    schema: {
31      type: 'object',
32      properties: {
33        schema: {
34          type: 'string',
35          description:
36            'Schema name containing the pgvector table (default: public).',
37        },
38        table: {
39          type: 'string',
40          description:
41            'Table used to store vectors and metadata (default: contractspec_vectors).',
42        },
43        createTableIfMissing: {
44          type: 'boolean',
45          description:
46            'Automatically create pgvector extension and table when first writing vectors.',
47        },
48        distanceMetric: {
49          type: 'string',
50          enum: ['cosine', 'l2', 'inner_product'],
51          description: 'Distance metric used for nearest-neighbor search.',
52        },
53      },
54    },
55    example: {
56      schema: 'public',
57      table: 'contractspec_vectors',
58      createTableIfMissing: true,
59      distanceMetric: 'cosine',
60    },
61  },
62  secretSchema: {
63    schema: {
64      type: 'object',
65      required: ['databaseUrl'],
66      properties: {
67        databaseUrl: {
68          type: 'string',
69          description:
70            'Supabase Postgres connection string with privileges to read/write vector rows.',
71        },
72      },
73    },
74    example: {
75      databaseUrl:
76        'postgresql://postgres.[project-ref]:password@aws-0-region.pooler.supabase.com:6543/postgres',
77    },
78  },
79  healthCheck: {
80    method: 'ping',
81    timeoutMs: 5000,
82  },
83  docsUrl: 'https://supabase.com/docs/guides/ai/vector-columns',
84  byokSetup: {
85    setupInstructions:
86      'Create or reuse a Supabase project, enable pgvector, and provide a Postgres connection string with read/write access to the target vector table.',
87  },
88});